In this paper, a fuzzy force control algorithm is suggested for commercialized industrial robots equipped with the position servo drives, where control rules of the proposed fuzzy controller are changed according to t...
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In this paper, a fuzzy force control algorithm is suggested for commercialized industrial robots equipped with the position servo drives, where control rules of the proposed fuzzy controller are changed according to the magnitude of environmental stiffness in such a way that good force response is maintained regardless of changes of environmental stiffness. Specifically, some fuzzy control rules are designed for several representative environmental stiffness values, and then a control action for a given arbitrary environmental stiffness value is decided by a fuzzy interpolation method. To show the validity of the proposed fuzzy controller, several experimental results are illustrated, where a 5-axis articulated robot manipulator equipped with the wrist force/torque sensor system and our prototype dual robot controller are employed.< >
In this paper, an approach to modelling of a robotic assembly cell is proposed and a method for managing the cell operation is described using a knowledge base. Since the modelling structure is based on the concept of...
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In this paper, an approach to modelling of a robotic assembly cell is proposed and a method for managing the cell operation is described using a knowledge base. Since the modelling structure is based on the concept of the state variable, the relationships between states are described by the state transition map (STM). The knowledge-bases for state transition and assembly job information are obtained from the STM and the assembly job tree (AJT), respectively. Using the knowledge-base, the system structure is discussed in relation to both managing the cell operation and evaluating the performances. Finally, a simulation algorithm is presented with the simulation results to show the significance of the proposed modelling approach.
An adaptive learning control approach is proposed which combines a mechanism to improve the control input sequence as well as to improve the learning control scheme based on the knowledge learned about the unknown sys...
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An adaptive learning control approach is proposed which combines a mechanism to improve the control input sequence as well as to improve the learning control scheme based on the knowledge learned about the unknown system and environment. The iterative learning control problem is treated from the 2D system point of view. A 2D model for a class of iterative learning control system is formulated. A learning gain estimator algorithm based on the 2D model is presented. The overall learning control system structure is given. The proposed learning control scheme does not require prior knowledge of the controlled system and has the ability to generalize the knowledge learned from one task operation to other tasks. This scheme can be applied to nonlinear system control problems. To demonstrate the feasibility of the proposed learning algorithm, simulation results on learning control for a three-water-tank system are given. The results show an excellent learning performance, even for nonrepetitive tasks.< >
An adaptive learning control approach is proposed that combines a mechanism to improve control input sequence as well as to improve the learning control scheme based on the knowledge learned about unknown system and e...
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An adaptive learning control approach is proposed that combines a mechanism to improve control input sequence as well as to improve the learning control scheme based on the knowledge learned about unknown system and environment. First, the iterative learning control problem is treated from the 2-D system point of view. A 2-D model for a class of iterative learning control systems is formulated. Then a learning gain estimator algorithm based on the 2-D model is presented. The overall learning control system structure is given.< >
The series Advances in Industrial control aims to report and encourage technology transfer in controlengineering. The rapid development of control technology has an impact on all areas of the control discipline. New ...
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ISBN:
(数字)9781846283345
ISBN:
(纸本)9781852339821;9781849969895
The series Advances in Industrial control aims to report and encourage technology transfer in controlengineering. The rapid development of control technology has an impact on all areas of the control discipline. New theory, new controllers, actuators, sensors, new industrial processes, computer methods, new applications, new philosophies , new challenges. Much of this development work resides in industrial reports, feasibility study papers and the reports of advanced collaborative projects. The series offers an opportunity for researchers to present an extended exposition of such new work in all aspects of industrial control for wider and rapid dissemination. In some areas of manufacturing, the elements of a flexible manufacturing system form the key components of the process line. These key components are four-fold: a set of programmable robots and machines, an automated materia- handling system that allows parts to be freely routed and re-routed, a buffer storage system where parts and partly-assembled components can wait until required for further processing and assembly and finally, a supervisory control system. The technology employed to coordinate and control all these components as a working system is usually based on programmable logic controllers. The use of this automation hardware and software in manufacturing is designed to yield significant cost reductions and to enhance quality.
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